
Understanding China through Big Data
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In each chapter of the book, the authors highlight an application of theory-guided macrosociology that has the potential to reinvigorate an ambitious, open-minded and bold approach to sociological research. These include social stratification, social networks, medical care, and online behaviours among many others. This research approach focuses on macro-level social process and phenomena by using quantitative models to statistically test for associations and causalities suggested by a clearly hypothesised social theory. By deploying theory-oriented macrosociology where it can best assure macro-level robustness and reliability, big data applications can be more relevant to and guided by social theory.
An essential read for sociologists with an interest in quantitative and macro-scale research methods, which also provides fascinating insights into Chinese society as a demonstration of the utility of its methodology.
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Guangye He is Associate Professor at Nanjing University, Department of Sociology. Her research focuses on family sociology, social stratification, and quantitative methodology in sociology. She has published in Social Science Research, Chinese Sociological Review, China Review, and Journal of Contemporary China.
Fei Yan is Associate Professor of Sociology at Tsinghua University. He received his Ph.D. in sociology from University of Oxford and completed a postdoc from Stanford University. His research focuses on political sociology, historical sociology, and sociology of development. His work has appeared in Social Science Research, The Sociological Review, Social Movement Studies, Poetics, Urban Studies, and Oxford Bibliographies in Sociology.
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